Evidence map›Paper›PMID 40382340›Full record

ArticleAnnals of medicine2025

Increased dialysis symptom index burden in maintenance hemodialysis patients during the COVID-19 lockdown period.

Wen-Man Zhao, Li Zhu, Yuyu Zhu, Xun-Liang Li, Rui Shi, Hai-Feng Pan, De-Guang Wang, Liang Yuan

Abstract read
In one paragraph

Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Wen-Man ZhaoDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Li ZhuDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Yuyu ZhuDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
Xun-Liang LiDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.ORCID 0000-0001-9964-2078
Rui ShiDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.ORCID 0000-0001-7400-9962
Hai-Feng PanDepartment of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China.ORCID 0000-0001-8218-5747
De-Guang WangDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.ORCID 0000-0003-4799-3241
Liang YuanDepartment of Nephrology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe high prevalence of dialysis-related symptoms in maintenance hemodialysis (MHD) patients severely affects their quality of life. Therefore, in this study, we assessed the dialysis symptom index (DSI) of MHD patients during the second wave of COVID-19, which triggered a health crisis, resulting in many cities in China opting for social isolation.

methodsA total of 106 MHD patients from our center were screened. DSI, sleep quality, and fatigue scales were investigated separately before and during lockdown. Demographic and laboratory data of MHD patients were collected. A nomogram was used to predict high DSI by combining multiple indicators. Additionally, internal validation was performed to reduce overfitting bias.

resultsThe mean age of patients was 56.0 years (SD 13.1). The prevalence and severity of DSI were significantly higher during lockdown than pre-lockdown. Notably, itching, trouble staying asleep, bone or joint pain, muscle cramps, feeling irritability, difficulty concentrating, headache, constipation, and feeling nervous were observed (

conclusionWe found a higher prevalence of DSI in MHD patients during the COVID-19 lockdown. Furthermore, patients with longer dialysis vintage, lower albumin levels, and Kt/V had a risk of developing high DSI.

Indexed as

COVID-19Kidney Failure, ChronicRenal DialysisAdultAgedChinaFatigueFemaleHumansMaleMiddle AgedPrevalenceQuality of LifeSARS-CoV-2Severity of Illness IndexSleep QualityCOVID-19dialysis system indexlockdownnomogram

Identifiers

PMID40382340
PMCPMC12086903

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.